Notes for Text Mining with R
Preface
I Text Mining with R
1 Tidy text format
2 Sentiment analysis with tidy data
3 Analyzing word and document frequency
4 Relationships between words: n-grams and correlations
- 4.1 Tokenizing by n-gram
- 4.2 Counting and correlating pairs of words with widyr
  - 4.2.1 Counting and correlating among sections
  - 4.2.2 Pairwise correlation
5 Converting to and from non-tidy formats
6 Topic modeling
7 Text classification
References
Appendix
A Reviews on regular expressions
B Text processing examples in R
Written with bookdown

Notes for “Text Mining with R: A Tidy Approach”

A Reviews on regular expressions

References:

Sams Teach Yourself Regular Expressions in 10 Minutes
https://regexr.com/